Predictive Analytics

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What is predictive analytics?

Predictive analytics combines historical data, machine learning algorithms, and statistical techniques to forecast future customer behaviors and trends. Predictive analytics predict customer needs, preferences, and actions – so businesses can create more personalized, effective marketing and customer engagement strategies.

Why is predictive analytics important?

With predictive analytics, businesses can deepen their understanding of customers, anticipate their needs, and engage them more effectively. It all adds up to higher satisfaction, loyalty, and revenue.

Benefits of predictive analytics

Predictive analytics determine the most effective next best action to engage a customer – whether that’s sending a personalized offer, following up on a service issue, or taking another relevant step.
Predictive analytics estimate the customer lifetime value, or future value a customer will bring to the business over their entire relationship. This informs business decisions about how much to invest in marketing activities.
Predictive analytics can identify customers who are at risk of churning based on their interaction patterns, purchase history, and engagement metrics. This allows companies to take proactive measures to retain at-risk customers.

How does predictive analytics work?

Predictive analytics takes steps involving data collection, data processing, model building, and implementation within AI-powered technology solutions. Businesses will walk away with increased efficacy in their marketing and customer engagement programs.